Marketing Research, Global Edition

Höfundar: Alvin C. Burns; Ann Veeck (Útgáfa: 10)
Marketing Research, Global Edition

Kaup valmöguleikar

For global marketing courses. A conceptual introduction to marketing research Marketing Research presents basic statistical techniques for analyzing market data, while equipping students with relevant job skills. Emphasizing practical applications, the authors explore global forces shaping marketing research today, including technological and philosophical influences such as AI and big data. The 10th Edition was condensed to focus on the most essential tools and concepts.

Nánar um bókina

Útgefandi
Pearson International Content
ISBN
9781292762746
Print ISBN
9781292495040
Format
ePub
Útgáfa
10
Höfundar
Alvin C. Burns; Ann Veeck
Tungumál
English
Útgefið
2026-02-03
Prent takmörkun á líftíma
100
Prent takmörkun
2
Afritunar takmörkun
2

Kaflar

  • Cover
  • Cover
  • Front Matter
  • Title Page
  • Copyright
  • Preface
  • About the Authors
  • Interactive Media Content
  • 1: Introduction to Marketing Research
  • Introduction: Introduction to Marketing Research
  • 1.1: Marketing Research Is Part of Marketing
  • 1.2: What Is Marketing Research?
  • 1.3: What Are the Uses of Marketing Research?
  • 1.4: Who Conducts Marketing Research?
  • 1.5: The Industry Structure
  • 1.6: Challenges of the Marketing Research Industry
  • 1.7: Industry Initiatives
  • 1.8: Industry Standards and Ethics
  • 1.9: A Career in Marketing Research
  • Summary: Introduction to Marketing Research
  • 2: The Marketing Research Process
  • Introduction: The Marketing Research Process
  • 2.1: The Marketing Research Process
  • 2.2: Defining the Problem
  • 2.3: Research Objectives
  • 2.4: Action Standards
  • 2.5: The Marketing Research Proposal
  • Summary: The Marketing Research Process
  • 3: Research Design
  • Introduction: Research Design
  • 3.1: Research Design
  • 3.2: Three Types of Research Design
  • 3.3: Exploratory Research
  • 3.4: Descriptive Research
  • 3.5: Causal Research
  • 3.6: Test Marketing
  • Summary: Research Design
  • 4: Secondary Data
  • Introduction: Secondary Data
  • 4.1: Big Data
  • 4.2: Primary versus Secondary Data
  • 4.3: Advantages and Disadvantages of Secondary Data
  • 4.4: Evaluating Secondary Data
  • 4.5: Classification of Secondary Data
  • 4.6: Published Sources and Official Data
  • 4.7: Syndicated Data
  • 4.8: Digital Data
  • 4.9: Big Data and Ethics
  • Summary: Secondary Data
  • 5: Qualitative Research Techniques
  • Introduction: Qualitative Research Techniques
  • 5.1: Quantitative, Qualitative, and Mixed Methods Research
  • 5.2: In-Depth Interviews
  • 5.3: Focus Groups
  • 5.4: Ethnographic Research
  • 5.5: Marketing Research Online Communities
  • 5.6: Observation Techniques
  • 5.7: Other Qualitative Research Techniques
  • 5.8: The Analysis of Qualitative Data
  • Summary: Qualitative Research Techniques
  • 6: Evaluating Survey Data Collection Methods
  • Introduction: Evaluating Survey Data Collection Methods
  • 6.1: Modes of Data Collection in Survey Research
  • 6.2: Online Surveys
  • 6.3: In-Person Surveys
  • 6.4: Paper Surveys
  • 6.5: Telephone Surveys
  • 6.6: Mixed-Mode Surveys
  • 6.7: Working with a Panel Company
  • 6.8: Choosing the Survey Method
  • Summary: Evaluating Survey Data Collection Methods
  • 7: Understanding Measurement, Developing Questions, and Designing the Questionnaire
  • Introduction: Understanding Measurement, Developing Questions, and Designing the Questionnaire
  • 7.1: Basic Measurement Concepts
  • 7.2: Types of Measures
  • 7.3: Interval Scales Commonly Used in Marketing Research
  • 7.4: Reliability and Validity of Measurements
  • 7.5: How to Design a Questionnaire
  • 7.6: Developing Questions
  • 7.7: Questionnaire Organization
  • 7.8: Computer-Assisted Questionnaire Design
  • 7.9: Finalize the Questionnaire
  • Summary: Understanding Measurement, Developing Questions, and Designing the Questionnaire
  • 8: Sample Size and Sample Selection
  • Introduction: Sample Size and Sample Selection
  • 8.1: Why Take a Sample?
  • 8.2: The Sample Size Formula
  • 8.3: Practical Considerations in Sample Size Determination
  • 8.4: Other Methods of Sample Size Determination
  • 8.5: Sampling Error
  • 8.6: Probability versus Nonprobability Sampling Methods
  • 8.7: Probability Sampling Methods
  • 8.8: Nonprobability Sampling Methods
  • 8.9: Online Sampling Techniques
  • 8.10: Developing a Sample Plan
  • Summary: Sample Size and Sample Selection
  • 9: Data Quality Issues and Datasets
  • Introduction: Data Quality Issues and Datasets
  • 9.1: Possible Respondent Errors in Data Collection
  • 9.2: Respondent Error Safeguards
  • 9.3: Nonresponse Error
  • 9.4: How Panel Companies Control Error
  • 9.5: Dataset and Coding Data
  • 9.6: Data Quality Issues
  • 9.7: SPSS Dataset, Data Code Book, and Operations
  • Summary: Data Quality Issues and Datasets
  • 10: Performing Descriptive Analysis, Computing Confidence Intervals, and Testing Hypotheses
  • Introduction: Performing Descriptive Analysis, Computing Confidence Intervals, and Testing Hypotheses
  • 10.1: Understanding Descriptive Analysis
  • 10.2: Reporting Descriptive Findings to Clients
  • 10.3: Statistical Inference: Sample Statistics and Population Parameters
  • 10.4: Parameter Estimation: Estimating the Population Percent or Mean
  • 10.5: Reporting Confidence Intervals to Clients
  • 10.6: Hypothesis Tests
  • 10.7: Using SPSS for Confidence Intervals and Hypothesis Tests for Proportions
  • Summary: Performing Descriptive Analysis, Computing Confidence Intervals, and Testing Hypotheses
  • 11: Implementing Basic Differences Tests
  • Introduction: Implementing Basic Differences Tests
  • 11.1: Why Differences Are Important
  • 11.2: Small Sample Sizes: The Use of a t Test or a z Test and How SPSS Eliminates the Worry
  • 11.3: Testing for Significant Differences Between Two Groups
  • 11.4: Testing for Significant Differences in Means Among More Than Two Groups: Analysis of Variance
  • 11.5: Reporting Group Differences Tests to Clients
  • 11.6: Differences Between Two Percents or Two Means Within the Same Sample (Paired Sample)
  • 11.7: Null Hypotheses for Differences Tests Summary
  • Summary: Implementing Basic Differences Tests
  • 12: Making Use of Associations Tests
  • Introduction: Making Use of Associations Tests
  • 12.1: Types of Relationships (Associations) Between Two Variables
  • 12.2: Characterizing Relationships Between Variables
  • 12.3: Correlation Coefficients and Covariation
  • 12.4: The Pearson Correlation Coefficient
  • 12.5: Caveats When Interpreting Correlations
  • 12.6: Reporting Correlation Findings to Clients
  • 12.7: Cross-Tabulations
  • 12.8: Chi-Square Analysis
  • 12.9: Communicating Cross-Tabulation Insights to Clients Using Data Visualization
  • 12.10: Special Considerations in Association Procedures
  • Summary: Making Use of Associations Tests
  • 13: Understanding Regression Analysis Basics
  • Introduction: Understanding Regression Analysis Basics
  • 13.1: Bivariate Linear Regression Analysis
  • 13.2: Multiple Regression Analysis
  • 13.3: Stepwise Multiple Regression
  • 13.4: Step-by-Step Summary of How to Perform Multiple Regression Analysis
  • 13.5: Communicating Regression Analysis Insights to Clients
  • 13.6: Warnings Regarding Multiple Regression Analysis
  • Summary: Understanding Regression Analysis Basics
  • 14: Communicating Insights
  • Introduction: Communicating Insights
  • 14.1: Why Insights?
  • 14.2: Characteristics of Effective Insights Communication
  • 14.3: The Traditional Marketing Research Report
  • 14.4: Guidelines for Tables and Visuals
  • 14.5: Discovering Insights
  • 14.6: Communicating Insights
  • 14.7: “Live” Presentation of Insights
  • 14.8: Disseminating Insights Throughout an Organization
  • Summary: Communicating Insights
  • Appendix: Case Studies
  • Case Study 1: Video Surveillance Research: New Insights Versus Ethics Issues
  • Case Study 2: Looking over the Average German Consumer’s Shoulder
  • Case Study 3: Big Data Shapes Tennis
  • Case Study 4: Your Supermarket Is Spying on You
  • Case Study 5: Automatic Question Answering: A Breakthrough in Market Surveys
  • Case Study 6: New Sources and Modes of Data for Market Research
  • Case Study 7: Biases in Ethical Work Behavior Research
  • Case Study 8: Meat Consumption in South Africa
  • Glossary